Image Processing Methods Applied to Motion Tracking of Nanomechanical Buckling on SEM Recordings

TL;DR

This paper presents an advanced image processing algorithm that leverages physical system knowledge to accurately track the motion of buckling nanomechanical structures in noisy SEM recordings, enabling detailed analysis of their dynamic behavior.

Contribution

The authors develop a physics-informed image processing method that improves motion tracking of NEMS buckling structures in SEM images with high noise levels, a novel approach in this context.

Findings

Successfully tracked NEMS motion in noisy SEM recordings.

Captured the relationship between deflection amplitude and compressive force.

Resolved transition from inter-well to intra-well motion in buckling NEMS.

Abstract

The scanning electron microscope (SEM) recordings of dynamic nano-electromechanical systems (NEMS) are difficult to analyze due to the noise caused by low frame rate, insufficient resolution and blurriness induced by applied electric potentials. Here, we develop an image processing algorithm enhanced by the physics of the underlying system to track the motion of buckling NEMS structures in the presence of high noise levels. The algorithm is composed of an image filter, two data filters, and a nonlinear regression model, which utilizes the expected form of the physical solution. The method was applied to the recordings of a NEMS beam about 150 nm wide, undergoing intra-and inter-well post-buckling states with a transition rate of approximately 0.5 Hz. The algorithm can track the dynamical motion of the NEMS and capture the dependency of deflection amplitude on the compressive force on the beam. With the help of the proposed algorithm, the transition from inter-well to intra-well motion is clearly resolved for buckling NEMS imaged under SEM.